582 search results - page 54 / 117 » Reinforcement learning with Gaussian processes |
133
Voted
ICASSP
2010
IEEE
15 years 3 months ago
2010
IEEE
Gaussian mixture models (GMMs) are a convenient and essential tool for the estimation of probability density functions. Although GMMs are used in many research domains from image ...
141
Voted
ATAL
2009
Springer
15 years 10 months ago
2009
Springer
One of the key problems in reinforcement learning is balancing exploration and exploitation. Another is learning and acting in large or even continuous Markov decision processes (...
112
Voted
PAMI
2008
15 years 3 months ago
2008
Mixture of Gaussians (MoG) model is a useful tool in statistical learning. In many learning processes that are based on mixture models, computational requirements are very demandin...
108
Voted
CIKM
2000
Springer
15 years 8 months ago
2000
Springer
We consider the problem of browsing the top ranked portion of the documents returned by an information retrieval system. We describe an interactive relevance feedback agent that a...
132
Voted
ICML
2009
IEEE
16 years 4 months ago
2009
IEEE
Reinforcement Learning methods for controlling stochastic processes typically assume a small and discrete action space. While continuous action spaces are quite common in real-wor...